Quantitative In situ Analysis of β-Catenin Expression in Breast Cancer Shows Decreased Expression Is Associated with Poor Outcome

Cancer Research - Tập 66 Số 10 - Trang 5487-5494 - 2006
Marisa Dolled‐Filhart1, Anthony McCabe2, Jennifer M. Giltnane2, Melissa A. Cregger2, Robert L. Camp2, David L. Rimm2
1Department of Pathology, Yale University School of Medicine, New Haven, Connecticut 06520, USA
2Department of Pathology, Yale University School of Medicine, New Haven, Connecticut

Tóm tắt

Abstract The role of β-catenin in breast cancer and its prognostic value is controversial. The prognostic value had been assessed previously in a series of nonquantitative immunohistochemical studies with conflicting results. In efforts to clarify the relationship between β-catenin protein expression and breast cancer prognosis, we have assessed a retrospective 600 case cohort of breast cancer tumors from the Yale Pathology archives on tissue microarrays. They were assessed using automated quantitative analysis (AQUA) with a series of array-embedded cell lines for which the β-catenin concentration was standardized by an ELISA assay. The expression levels of the standard clinical markers HER2, estrogen receptor (ER), progesterone receptor (PR), and Ki-67 were also assessed on the same cohort. X-tile software was used to select optimal protein concentration cutpoints and to evaluate the outcome using a training set and a validation set. We found that low-level expression of membranous β-catenin is associated with significantly worse outcome (38% versus 76%, 10-year survival, validation set log-rank P = 0.0016). Multivariate analysis of this marker, assessed in a proportional hazards model with tumor size, age, node status, nuclear grade, ER, PR, HER2, and Ki-67, is still highly significant with a hazard ratio of 6.8 (P < 0.0001, 95% confidence interval, 3.1-15.1). These results suggest that loss of β-catenin expression at the membrane, as assessed by objective quantitative analysis methods, may be useful as a prognostic marker or may be part of a useful algorithm for prognosis in breast cancer. (Cancer Res 2006; 66(10): 5487-94)

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